Summary

AHgen (Abstraction Hierarchy Generator) is an R package to generate, analyse, compare, and visualise Abstraction Hierarchies. AHgen was developed as part of the Water Resilient Cities project (EPSRC EP/N030419/1), to compare Urban Systems Abstraction Hierarchy (USAH) scenarios for UK cities using outputs from OSMtidy. Its functions may be applied to analyse Abstraction Hierarchies in any domain or at any scale.

Statement of need

AHgen (Abstraction Hierarchy Generator) is an R package to generate, analyse, compare, and visualise Abstraction Hierarchies. The Abstraction Hierarchy is a method from the discipline of human factors, as one part of the Cognitive Work Analysis framework (Jenkins, Stanton, and Walker (2009)). Originally developed to improve the design of safety-critical work systems (e.g., a nuclear power plant), this has also been applied to map and explore systems at any scale – from microwaves to transport systems to entire cities.

The Abstraction Hierarchy is a hierarchical network, wherein:

Figure 1. Example - Urban Systems Abstraction Hierarchy.
Figure 1. Example - Urban Systems Abstraction Hierarchy.

At the bottom of the hierarchy are the Resources (Level 5). These object types are linked to Processes (Level 4) they support, then to Tasks (Level 3) they achieve, then to Outcomes (Level 2), and finally to Purposes (Level 1). These system parts are nodes, which are linked between levels through their functionality, connecting the physical to the abstract. Moving upward through the levels the nodes are connected by asking ‘why the node exists’; moving downward levels the nodes are connected by asking ‘how a node is afforded’. These links represent the ‘means’ that a system can use to achieve defined ‘ends’, explicitly connecting the physical and abstract. By understanding how physical objects connect to different – yet interdependent – functions, we can improve the design of the system.

Historically, applications of the Abstraction Hierarchy method aimed to visualise and inspect the network, relying on pen-and-paper methods, PowerPoint drawing, or proprietary software. AHgen brings the Abstraction Hierarchy into the 21st century with an open source software code in R. This enables a user to not only quickly and repeatably visualise the network, but also modify and analyse it in a standardised manner.

AHgen was developed as part of the Water Resilient Cities project (EPSRC EP/N030419/1). The project developed an Urban Systems Abstraction Hierarchy (USAH) template (Bedinger et al. (2020); McClymont et al. (2022)), to enable comparisons between UK cities using outputs from OSMtidy. Its functions may be applied to Abstraction Hierarchies in any domain or at any scale.

AHgen is extremely flexible, with many possible workflows. There are five families of functions:

  1. Input Reading in the Abstraction Hierarchy and accompanying data
  2. Convert Converting the Abstraction Hierarchy into formats compatible with network analysis in R
  3. Weight Weighting edges
  4. Analyse Applying network analysis, plus summarising, comparing, and exporting outputs
  5. Visualise Visualising the Abstraction Hierarchy and results
Figure 2. AHgen workflow.
Figure 2. AHgen workflow.

AHgen was designed to be used both by researchers and students, across human factors, climate impacts, and more. It has been used in a number of scientific publications (e.g. Beevers et al. (2022a), Beevers, McClymont, and Bedinger (2022b), McClymont et al. (2023), Bedinger et al. (2023)). It has also been used in international research projects, and undergraduate and postgraduate research dissertations. Some AHgen functions have wider applications for network analysis in any domain. For example, the function sbc_norm() was developed based on the work of Segarra and Ribeiro (2014) to calculate Stable Betweenness Centrality, a metric for which there does not appear to be an existing function in the R ecosystem. In a teaching environment, AHgen can be used in courses related to human factors and systems analysis.

AHgen is supported by vignettes that provide the background to its development, clear installation instructions, step-by-step tutorials to introduce and demonstrate functions, and beginner guidance on the interpretation of network analysis results for Abstraction Hierarchies. It was also designed to accommodate future developments, such as the inclusion of additional network metrics and more sophisticated network representations such as hypergraphs.

Acknowledgements

AHgen was developed to compare Urban Systems Abstraction Hierarchy (USAH) scenarios for UK cities as part of the Water Resilient Cities project (EPSRC EP/N030419/1).

References

Bedinger, Melissa, Lindsay Beevers, Guy H. Walker, Annie Visser-Quinn, and Kerri McClymont. 2020. “Urban Systems: Mapping Interdependencies and Outcomes to Support Systems Thinking.” Journal Article. Earth’s Future 8 (3): e2019EF001389. https://doi.org/http://dx.doi.org/10.1029/2019EF001389.
Bedinger, Melissa, Kerri McClymont, Lindsay Beevers, Annie Visser-Quinn, and Gordon Aitken. 2023. “Five Cities: Application of the Urban Systems Abstraction Hierarchy to Characterize Resilience Across Locations.” Journal Article. Cities 139: 104335. https://doi.org/https://doi.org/10.1016/j.cities.2023.104355.
Beevers, Lindsay, Melissa Bedinger, Kerri McClymont, David Morrison, Gordon Aitken, and Annie Visser-Quinn. 2022a. “Modelling Systemic COVID-19 Impacts in Cities.” Journal Article 2 (2022a): 17. https://doi.org/https://doi.org/10.1038/s42949-022-00060-2.
Beevers, Lindsay, Kerri McClymont, and Melissa Bedinger. 2022b. “A Hazard-Agnostic Model for Unpacking Systemic Impacts in Urban Systems.” Journal Article 39 (3): 224–41. https://doi.org/https://doi.org/10.1080/10286608.2022.2083112.
Jenkins, Daniel P., Neville A. Stanton, and Guy H. Walker. 2009. Cognitive Work Analysis: Coping with Complexity. Book. London: CRC Press. https://doi.org/https://doi.org/10.1201/9781315572543.
McClymont, Kerri, Melissa Bedinger, Lindsay Beevers, and Guy Walker. 2022. “Understanding Urban Resilience with the Urban Systems Abstraction Hierarchy.” Journal Article. Sustainable Cities and Society 80: 103729. https://doi.org/https://doi.org/10.1016/j.scs.2022.103729.
McClymont, Kerri, Melissa Bedinger, Lindsay Beevers, and Guy H. Walker. 2023. “Applying the Urban Systems Abstraction Hierarchy as a Tool for Flood Resilience.” Journal Article 11 (5): e2023EF003594. https://doi.org/https://doi.org/10.1029/2023EF003594.
Segarra, Santiago, and Alejandro Ribeiro. 2014. “A Stable Betweenness Centrality Measure in Networks.” Conference Paper. https://doi.org/https://doi.org/10.1109/ICASSP.2014.6854324.